Results 41 to 50 of about 452,503 (268)
Projection Pursuit Multivariate Sampling of Parameter Uncertainty
Applied Sciences, 2022 The efficiency of sampling is a critical concern in Monte Carlo analysis, which is frequently used to assess the effect of the uncertainty of the input variables on the uncertainty of the model outputs.
Oktay Erten +2 more
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Multiple Response Variables Regression Models in R: The mcglm Package
Journal of Statistical Software, 2018 This article describes the R package mcglm implemented for fitting multivariate covariance generalized linear models (McGLMs). McGLMs provide a general statistical modeling framework for normal and non-normal multivariate data analysis, designed to ...
Wagner Hugo Bonat
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A new approach fits multivariate genomic prediction models efficiently
Genetics Selection Evolution, 2022 Background Fast, memory-efficient, and reliable algorithms for estimating genomic estimated breeding values (GEBV) for multiple traits and environments are needed to make timely decisions in breeding.
Alencar Xavier, David Habier
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Molecular Oncology, EarlyView.Combining PTEN protein assessment and transcriptomic profiling of prostate tumors, we uncovered a network enriched in senescence and extracellular matrix (ECM) programs associated with PTEN loss and conserved in a mouse model. We show that PTEN‐deficient cells trigger paracrine remodeling of the surrounding stroma and this information could help ...
Ivana Rondon‐Lorefice +16 more
wiley +1 more source
Variable Selection and Inference for Multi-Period Forecasting Problems [PDF]
, 2009 This paper conducts a broad-based comparison of iterated and direct multi-step forecasting approaches applied to both univariate and multivariate models.
Pesaran, Mohammad Hashem +2 more
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Generalized least squares estimation of the functional multivariate linear errors-in-variables model
Journal of Multivariate Analysis, 1986 The method of generalized least squares is applied to the sample matrix of mean squares and products to obtain estimators of the parameters of the functional multivariate linear errors-in-variables model. These estimators are shown to be consistent and asymptotically multivariate normal. Relationships between generalized least squares estimation of the
Dahm, P.Fred, Fuller, Wayne A
openaire +2 more sources
Targeted modulation of IGFL2‐AS1 reveals its translational potential in cervical adenocarcinoma
Molecular Oncology, EarlyView.Cervical adenocarcinoma patients face worse outcomes than squamous cell carcinoma counterparts despite similar treatment. The identification of IGFL2‐AS1's differential expression provides a molecular basis for distinguishing these histotypes, paving the way for personalized therapies and improved survival in vulnerable populations globally.
Ricardo Cesar Cintra +6 more
wiley +1 more source
BarekengMulti-Output Machine Learning is an advancement of traditional machine learning, designed to predict multiple output variables simultaneously while considering the relationships between these output variables.
Karin Joan, Robyn Irawan, Benny Yong
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IATSS Research, 2021 Road safety modeling enables the development of crash prediction models and the investigation of which factors contribute to crash occurrence. Developing multivariate response models is also valuable, but such models are currently under-exploited ...
Philippe Barbosa Silva +2 more
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FEBS Open Bio, EarlyView.ERα splice variant ERα∆7 lacks the C‐terminus, and its expression may change phenotypes of breast cancers. Our results showed that ERα∆7 is found in the luminal A subtype, and elevated ERα∆7 levels are linked to improved cell survival with lower proliferation and migration.
Long Wai Tsui +10 more
wiley +1 more source